Compara mètodes

	Model de Mescla de Creixement (GMM)	Anàlisi Factorial Exploratòria (EFA)
Camp	Estadística	Estadística
Família	Latent structure	Latent structure
Any d'origen	1999	—
Autor original	Bengt O. Muthén & Kerby Shedden	—
Tipus	Latent class / longitudinal growth model	Latent variable / dimension reduction
Font seminal	Muthén, B. O. & Shedden, K. (1999). Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm. Biometrics, 55(2), 463–469.	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.
Àlies	Büyüme Karışım Modeli (Growth Mixture Model — GMM), GMM, latent class growth analysis extension, mixture latent growth curve model	common factor analysis, açımlayıcı faktör analizi, factor analysis
Relacionats	5	4
Resum	The Growth Mixture Model, introduced by Muthén and Shedden in 1999, is a longitudinal latent variable method that identifies distinct subpopulations — latent trajectory classes — each following its own growth curve over time. It extends the standard Latent Growth Curve (LGC) model by allowing the sample to be composed of an unknown mixture of classes with different intercepts, slopes, and variance structures.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.